The rapid progress in informatisation and electrification in transportation has gradually transferred public transport junctions such as metro stations into the nexus of pedestrian flows, information flows, computation flows and energy flows. These smart environments that are efficient in handling large volume passenger flows in routine circumstances can become even more vulnerable during emergency situations and amplify the losses in lives and property owing to power outage triggered service degradation and destructive crowed behaviours. On the bright side, the increasingly abundant resources contained in smart environments have enlarged the optimisation space of an evacuation process, yet little research has concentrated on the joint optimal resource allocation between transportation infrastructures and pedestrians. Hence, in the paper, we propose a queueing network based resource allocation model to comprehensively optimise various types of resources during emergency evacuations. Experiments are conducted in a simulated metro station environment with realistic settings. The simulation results show that the proposed model can considerably improve the evacuation efficiency as well as the robustness of the emergency response system during emergency situations.
Large-scale activities such as the Winter Olympics are usually held in areas with low temperature or other harsh environments, which greatly affects the spectating experience of pedestrians. In order to improve the travel efficiency and reduce the safety risk of pedestrians, an adaptive information-distribution strategy of VMS (variable message sign) for road networks is proposed to guide the pedestrians. In the proposed strategy, the dynamic feedback mechanism between the VMS information distribution and the state of crowded pedestrians is established, and the dynamic optimization model of the VMS information release layout is formulated. To evaluate the effectiveness of the strategy, a multiagent-based simulation method is proposed. Through numerical simulation, it is found that the guidance strategy can improve the movement efficiency by adjusting releasing duration of VMS information or improving the information obedience rate of pedestrians. In this paper, a large-scale competition area in the Xiaohaituo Mountain in Beijing was taken as an example to simulate the scenarios of ingress and egress with and without the strategy. The results show that the average walking time and the road congestion can be significantly reduced in the road network with the strategy, and the proportion of pedestrians with shorter travel time can be increased. Therefore, the research can provide theoretical foundation and data support for managers to guide passenger flows and improve the spectating experience.
This paper investigates the internal mechanism of the trucker’s willingness to use familiar roads by constructing a structural equation model of road loyalty, in which the influence of the trucker’s “emotional value” is additionally considered. The proposed method can be used to understand the trucker’s psychological needs to improve the level of road service. Based on questionnaire data, AMOS software was used to analyze the correlations and corresponding parameters among 10 latent variables and 30 explicit variables. The model results show that, in addition to the value of roads as a commodity, the emotional dependence of truckers in the process of using them also has an impact on the perceived value of road services. The results of model index scores show that truck drivers’ loyalty to the road does not represent their satisfaction, and familiarity with the road is still “forced” to be the first choice of most truckers due to the cost and trust in the reliability of unfamiliar roads when the road service quality and experience do not meet truckers’ expectations. The latent variable scores indicate that improvements in “road safety” and “costs” are the key points to improve truckers’ overall satisfaction with road freight access.
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